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Elie Bismuth

I put AI in production and generate revenue

I take an idea and ship it to production — battle-tested at Doctrine, HireSweet and Topo.io (YC 2024).

€0M+
ARR generated
0
years of experience
0
SaaS shipped

Trusted by

Doctrine logoTopo logoY Combinator logoHireSweet logo

Proven results in production

Flow Counsel — AI-Powered Contract Analysis

~1M€ ARRrevenue generated400daily active users5 000analyses / day

Doctrine is France's leading legal intelligence platform, used by over 20,000 legal professionals. The company wanted to expand into the contracts space, but had no defined product direction.

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Topo — Collaborative Sales Rooms for B2B

YC W24Y Combinator1erengineer hired

Topo.io is a collaborative workspace for B2B sales teams: digital sales rooms that help sellers better engage buyers and deliver a modern buying experience.

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HireSweet — Tech Talent Matching & Recruitment Platform

300+daily active clients-50%Ops processing time

HireSweet operated two complementary products in tech recruitment: Discover, a marketplace of qualified candidates presented weekly to companies, and Reveal, a SaaS ATS to centralize and automate candidate database management.

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I don't code features. I build products.

Every technical decision I make starts with a simple question: what's the impact for the user and for the business? Choosing a framework, designing an API, integrating an AI model — everything goes through that filter. The most elegant tech in the world is worthless if it doesn't solve a real problem.

I'm constantly looking for the right balance between quality and velocity. No technical debt out of laziness, but no over-engineering out of ego either.

When I join a team, I truly integrate. I read the codebase before proposing changes. I adopt your practices before suggesting new ones. And I leave the project in a better state than I found it.

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What I ship with in production

14 technologies, 3 products shipped at startups & scaleups — from API to monitoring.

Frontend / Product

  • TypeScript — End-to-end strict mode, from API to frontend
  • React / Next.js — Production apps at Doctrine, Topo (YC W24), HireSweet
  • GraphQL — Typed APIs with client code generation

Backend

  • Node.js / NestJS — Production microservices and modular monoliths
  • PostgreSQL / MongoDB — Relational and document modeling driven by business needs
  • Queues & Caches — Redis, SQS — async jobs and application caching

AI / LLM

  • OpenAI, Anthropic Claude — Production LLM integrations with prompt engineering
  • RAG & Embeddings — Retrieval-augmented pipelines for domain data
  • Agents (CrewAI, LangChain, LangGraph) — Multi-agent AI workflow orchestration
  • BMAD & Spec-Driven Development — Structured methodology to drive AI agents end-to-end

Infrastructure / Observability

  • AWS — Multi-service cloud deployments at startups
  • Datadog — Application monitoring, alerting and observability
  • Sentry — Production error tracking and performance monitoring
  • Docker & Kubernetes — Containerization and orchestration in startup environments

Let's discuss your next AI product

30 minutes free, no commitment.